Current Characteristics Research Articles

Impact of Oxide Charges on The Minority Carrier Response in MOS(p) Devices With Al2O3/SiO2 Gate Stacks under Strong Inversion Condition

In this study, a compact model proposed in the previous work (2) was utilized to elucidate an unusual minority carrier response time observed in MOS(p) devices with Al2O3/SiO2 gate stacks. It is supposed that the number of oxide charges increases with SiO2 thickness. The findings confirmed the heightened sensitivity of device alternating current (AC) characteristics to oxide charges in the outer region. Accordingly, we explored the dependencies of oxide thickness and quality on the transition frequency (ωm) of devices.

A review of occurrence, bioaccumulation, and fate of novel brominated flame retardants in aquatic environments: A comparison with legacy brominated flame retardants.

Novel brominated flame retardants (NBFRs) have been developed as replacements for legacy brominated flame retardants (BFRs) such as polybrominated diphenyl ethers (PBDEs) and hexabromocyclododecanes (HBCDs). The prevalence of NBFRs in aquatic environments has initiated intense concerns that they resemble to BFRs. To comprehensively elucidate the fate of NBFRs in aquatic environments, this review summarizes the physico-chemical properties, distribution, bioaccumulation, and fates in aquatic environments. 1,2-Bis(2,3,4,5,6-pentabromophenyl) ethane (DBDPE) as the major substitute for PBDEs is the primary NBFR. The release from industrial point sources such as e-waste recycling stations is the dominant way for NBFRs to enter the environment, which results in significant differences in the regional distribution of NBFRs. Sediment is the major sink of NBFRs attributed to the high hydrophobicity. Significantly, there is no decreasing trend of NBFRs concentrations, while PBDEs achieved the peak value in 1970-2000 and decreased gradually. The bioaccumulation of NBFRs is reported in both field studies and laboratory studies, which is regulated by the active area, lipid contents, trophic level of aquatic organisms, and the log KOW of NBFRs. The biotransformation of NBFRs showed similar metabolism patterns to that of BFRs, including debromination, hydroxylation, methoxylation, hydrolysis, and glycosylation. In addition, NBFRs show great potential in trophic magnification along the aquatic food chain, which could pose a higher risk to high trophic-level species. The passive uptake by roots dominates the plant uptake of NBFRs, followed by acropetal and basipetal bidirectional transportation between roots and leaves in plants. This review will provide the support to understand the current pollution characteristics of NBFRs and highlight perspectives for future research.

Prediction of electrical properties of GAAFET based on integrated learning model

As device feature sizes continue to decrease and fin field effect transistors reach their physical limits, gate all around field effect transistors (GAAFETs) have emerged with larger gate control areas and stackable characteristics for better suppression of second-order effects such as short-channel effects due to their gate encircling characteristics. Traditional methods for studying the electrical characteristics of devices are mostly based on the technology computer-aided design. Still, it is not conducive to developing new devices due to its time-consuming and inefficient drawbacks. Deep learning (DL) and machine learning (ML) have been well-used in recent years in many fields. In this paper, we propose an integrated learning model that integrates the advantages of DL and ML to solve many problems in traditional methods. This integrated learning model predicts the direct current characteristics, capacitance characteristics, and electrical parameters of GAAFET better than those predicted by DL or ML methods alone, with a linear regression factor (R 2) greater than 0.99 and very small root mean square error. The proposed integrated learning model achieves fast and accurate prediction of GAAFET electrical characteristics, which provides a new idea for device and circuit simulation and characteristics prediction in microelectronics.

Evaluating factors associated with telehealth appropriateness in outpatient rheumatoid arthritis encounters using the Encounter Appropriateness Score for You (EASY).

Telehealth has been proposed as a safe and effective alternative to in-person care for rheumatoid arthritis (RA). The purpose of this study was to evaluate factors associated with telehealth appropriateness in outpatient RA encounters. A prospective cohort study (1/1/21-8/31/21) was conducted using electronic health record data from outpatient RA encounters in a single academic rheumatology practice. Rheumatology providers rated the telehealth appropriateness of their own encounters using the Encounter Appropriateness Score for You (EASY) immediately following each encounter. Robust Poisson regression with Generalized Estimating Equations (GEE) modeling was used to evaluate the association of telehealth appropriateness with patient demographics, RA clinical characteristics, comorbid non-inflammatory causes of joint pain, previous and current encounter characteristics, and provider characteristics. During the study period, 1,823 outpatient encounters with 1,177 unique RA patients received an EASY score from 25 rheumatology providers. In the final multivariate model [Relative Risk (95% Confidence Interval)], factors associated with increased telehealth appropriateness included higher average provider preference for telehealth in prior encounters [1.26 (1.21-1.31)], telehealth as the current encounter modality [2.27 (1.95-2.64)], and increased patient age [1.05 (1.01-1.09)]. Factors associated with decreased telehealth appropriateness included moderate [0.81 (0.68-0.96)] and high [0.57 (0.46-0.70)] RA disease activity and if the previous encounter were conducted via telehealth [0.83 (0.73-0.95)]. In this study, telehealth appropriateness was most associated with provider preference, the current and previous encounter modality, and RA disease activity. Other factors like patient demographics, RA medications, and comorbid non-inflammatory causes of joint pain were not associated with telehealth appropriateness.

Where Do We Go From Here? An Inventory of Publicly Available Data About Educator Academies, Medical Education Departments, and Offices of Medical Education.

With the recent widespread growth and interest among medical educators, analysis of how departments of medical education are structured and their intersection with existing structures within the same institution, such as an office of medical education and/or academy of educators, is warranted. Based on a review of the literature, the authors determined there was a need for an inventory of what medical schools have to offer their faculty, whether it be an office, an academy, or a department. This project sought to inventory the current structures of medical education departments, offices, and academies at U.S. medical schools to explore reporting structure, functions, and characteristics of these entities. Data were extracted from the A Snapshot of Medical Student Education in the United States and Canada: Reports From 145 Schools, published in 2020 in the journal Academic Medicine, for each reporting institution. This led to exploration of medical school websites to catalog institutional structures. Data collected in this inventory demonstrate the range of structures used by medical schools to offer faculty support for their work as teachers and educational researchers. The hypothesis was that departments of medical education would be the least prevalent structures identified in U.S. medical schools, which was indeed a finding. Although the search yielded considerable data for the inventory, there is a dearth of published literature describing current models and characteristics of these different entities. Significant difficulties were encountered locating information clearly delineating roles and responsibilities of each entity on many medical schools' public-facing web pages. Findings are significant because they underscore the challenges medical education leaders have in obtaining information to research, compare, select, and design the administrative model(s) best suited to support faculty educators at their institution. Future work should include creating a detailed catalogue with descriptive information supplied by schools.

Stabilization of Morphotropic Phase Boundary in Hafnia Via Microwave Low‐temperature Crystallization Process for Next‐generation DRAM Technology

The morphotropic phase boundary (MPB), which arises from the combination of antiferroelectric and ferroelectric phases, demonstrates the highest dielectric constant (κ) compared to other phases. This emphasizes its potential as a leading contender for dielectric films in future DRAM capacitors. MPB‐based high‐κ materials using hafnia have shown a trade‐off between equivalent oxide thickness (EOT) and leakage current density (Jleak) when the crystallization temperature increases with scaling the thickness. In this study, we employed a microwave annealing (MWA) method that can achieve low‐temperature crystallization below 350 °C. The purpose of this method is to mitigate the trade‐off relationships and achieve the strict criteria of current DRAM capacitors. These criteria include low EOT (less than 4 Å) and Jleak (less than 10‐7 A/cm2 at 0.8 V) characteristics. The MWA is capable of relatively low‐temperature annealing by supplying energy to the films through both thermal energy and dipole vibration energy. As a result, we achieved a record low EOT of 3.76 Å and a low leakage current characteristic of 4.2×10‐8 A/cm2 at 0.8 V concurrently. We are confident that our research can be important in addressing the challenges associated with reducing the size of next‐generation DRAM capacitors.This article is protected by copyright. All rights reserved.

Ga2O3 Photon‐Controlled Diode for Sensitive DUV/X‐Ray Detection and High‐Resolution Array Imaging Application

AbstractSensitive high‐energy photon detection from UV to X‐ray and high‐resolution array imaging are critical for medical diagnosis, space exploration, and scientific research. The key challenges for high‐performance photodetector and imaging arrays are the effective material and device design strategies for the miniaturization and integration of the device. Here, photon‐controlled diodes (i.e., the detector has rectifying characteristics only under light irradiation) are proposed for high‐resolution and anti‐crosstalk array imaging applications without integrating the switching element. Based on ultra‐wide bandgap semiconductor Ga2O3, the sensitive DUV/X‐ray photon‐controlled diodes are realized by the design of high‐resistance Ga2O3 film and high‐barrier contact. The device exhibits remarkable detection performance, including high photo‐responsivity (168 A W−1) and specific detectivity (1.45 × 1015 Jones) under DUV illumination, as well as a high sensitivity (1.23 × 105 µC Gyair−1 cm−2) under X‐ray light. Moreover, the low dark current and excellent rectification characteristics are obtained. Furthermore, its potential for high‐density and anti‐crosstalk array imaging applications is verified. These results not only bring forth new insights in the implementation of high‐performance DUV/X‐ray photodetector, but also pave a feasible way to realize high pixel density detector array through the simplified fabrication process for high‐resolution imaging applications.

Characterization and mid-term outcomes of current out-of-hospital cardiac arrest patients admitted to intensive cardiovascular care units

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Consell Català de Resuscitació. Background Out-of-hospital cardiac arrest (OHCA) accounts the 50% of cardiovascular deaths. Being aware of characteristics and outcomes of our OHCA population is important in order to apply measures in the weaker areas to improve the results of the process. Purpose To investigate current outcomes, at 6-month follow-up, of patients admitted to an Intensive Cardiac Care Unit (ICCU) in a mediterranean area during the 2020s. Current characteristics, prehospital management and factors related to outcomes were also analyzed. Methods PCR-Cat was a prospective observational multicentre registry. OHCA patients admitted to the ICCU of 8 hospitals were included from October/2020 to December/2021. Those who survived with good neurological status, no disabilities, and remained independent for usual life activities, were classified as Good Outcome (GO). Those patients who died or had a poor neurological status, with high dependency or rested in permanent vegetative status were classified as Poor Outcome (PO). A multinomial logistic regression was done to analyze the factors independently related to PO. Results 288 patients were included, only 50 (17.36%) were women. At 6-month follow-up, 48.95% of patients had GO. Most events happened in the first month (Figure 1). The cause of death was neurological in 72.9%. Patients with PO were significantly older (63.74 vs. 58.88, p=0.003) and had more comorbidities (Table 1A). The most frequent location was on a public space (54.84%) and most were witnessed (88.93%). Cardiopulmonary resuscitation maneuvers were initiated by a bystander in 69.18% until EMS arrival, being only 20.79% done by an experienced bystander. The medium no-flow time was low (2 min) but total time until ROSC was of 28 min. First rhythm was shockable in 80%, but an automatic external defibrillator was only used in 58% of cases. Statistically significant lower values of first pH and higher values of first lactate, glucose and creatinine were related to PO (Table 1B). Patients with PO had a higher APACHE II (26 vs. 20, p<0.001) and SOFA (10.39 vs. 7.14, p<0.001) scores at admission, and required a longer time on mechanical ventilation (6 vs. 3.5 days, p=0.001). The main cause of the OHCA was acute coronary syndrome (53.82%), followed by chronic coronary syndrome (7.64%) and dilated myocardiopathy (7.64%). In the multinomial logistic regression, older age (p=0.005), male sex (p=0.016), previous stroke (p=0.046), longer ROSC time (p<0.001) and non-shockable first rhythm (p<0.001) were independently related to PO. Receiving cardiopulmonary resuscitation maneuvers by an experienced bystander was related to a reduction of 17 min of ROSC (p=0.001). Conclusions Less than a half of patients admitted to an ICCU because of an OHCA had GO at 6-month follow-up. Age, male sex, previous stroke, longer ROSC time and non-shockable first rhythm were factors independently related to PO. Interventions addressed to reduce ROSC time are urgently needed.

Exploring Intertwined quantum and cryogenic behaviour in ultra-scaled 10 nm MOSFET: a NEGF quantum ballistic simulation

Silicon-based spin qubits have emerged as promising candidates for scalable quantum information processing. This study first time investigates the behaviour of ultra-scaled 10 nm gate length and 3 nm channel thickness nanoscale double gate metal-oxide semiconductor field-effect transistors (MOSFETs) over a broad temperature range, from deep cryogenic (4 K) to room temperature (300 K). Employing the Non-Equilibrium Green’s Function (NEGF) method, the research explores the intertwined quantum and cryogenic behaviours of the various quantum phenomena, including eigen energies, eigen-functions, electron concentration, current characteristics, and more. This comprehensive analysis sheds light on the intricate interplay of quantum effects in nanoscale transistors under deep cryogenic conditions, offering valuable insights into the development of cryo-CMOS circuits for quantum computing.

Precision forecasting of grinding wheel Wear: A TransBiGRU model for advanced industrial predictive maintenance

In intelligent manufacturing, accurate prediction of grinding wheel wear is essential to reduce maintenance costs and improve production efficiency. To achieve accurate forecasts, this paper introduces a grinding wheel wear prediction model, TransBiGRU, incorporating a Transformer encoder, Bidirectional Gated Recurrent Unit (BiGRU), positional encoding layer, and position-wise feedforward layer. The model extracts features by analyzing current signal characteristics in basic statistical, time, and frequency domains during the machining process. Training is conducted through K-fold cross-validation to ensure model stability. The experimental results indicate that the model achieved good performance with Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Coefficient of Determination (R2) evaluation metrics, obtaining values of 2.0898, 3.262, and 0.9338, respectively. Systematically reducing modules validates the importance of each module in enhancing predictive capabilities. This research achieves the practical application of low-cost current sensors in optimizing maintenance plans and reducing downtime in predicting grinding wheel wear.

Development and validation of machine learning models to predict unplanned hospitalizations of patients with diabetes within the next 12 months

BACKGROUND: The incidence of diabetes mellitus (DM) both in the Russian Federation and in the world has been steadily increasing for several decades. Stable population growth and current epidemiological characteristics of DM lead to enormous economic costs and significant social losses throughout the world. The disease often progresses with the development of specific complications, while significantly increasing the likelihood of hospitalization. The creation and inference of a machine learning model for predicting hospitalizations of patients with DM to an inpatient medical facility will make it possible to personalize the provision of medical care and optimize the load on the entire healthcare system.AIM: Development and validation of models for predicting unplanned hospitalizations of patients with diabetes due to the disease itself and its complications using machine learning algorithms and data from real clinical practice.MATERIALS AND METHODS: 170,141 depersonalized electronic health records of 23,742 diabetic patients were included in the study. Anamnestic, constitutional, clinical, instrumental and laboratory data, widely used in routine medical practice, were considered as potential predictors, a total of 33 signs. Logistic regression (LR), gradient boosting methods (LightGBM, XGBoost, CatBoost), decision tree-based methods (RandomForest and ExtraTrees), and a neural network-based algorithm (Multi-layer Perceptron) were compared. External validation was performed on the data of the separate region of Russian Federation.RESULTS: The best results and stability to external validation data were shown by the LightGBM model with an AUC of 0.818 (95% CI 0.802–0.834) in internal testing and 0.802 (95% CI 0.773–0.832) in external validation.CONCLUSION: The metrics of the best model were superior to previously published studies. The results of external validation showed the relative stability of the model to new data from another region, that reflects the possibility of the model’s application in real clinical practice.

Feedback control system for vibration construction of fresh concrete

To address the issue of uncontrolled vibration in concrete construction. A control system with visual and auditory feedback functionality is developed. Worker posture is represented by Euler angles and size of body to establish palm positioning model. Combined with the construction characteristic of the vibrator, the position relationship between the worker head and vibrator tip is established using the palm as medium. The working state judgment algorithm for vibrator is proposed using the variation characteristic of input current in vibrator to calculate the vibration duration and insertion depth. Based on these algorithms, developing devices are suitable for manual vibration to collect calculated parameters. The developed software system accesses parameters from on-site devices to evaluate vibration quality based on energy transfer model, and sends the construction warning information to site through visualization model and the main control device installed on safety helmet. The application proves that the developed feedback control system is helpful to improve the vibration quality.

Influence of the Dielectric Constant on the Ionic Current Rectification of Bipolar Nanopores.

In this paper, we investigate how the dielectric constant, ϵ, of an electrolyte solvent influences the current rectification characteristics of bipolar nanopores. It is well recognized that bipolar nanopores with two oppositely charged regions rectify current when exposed to an alternating electric potential difference. Here, we consider dilute electrolytes with NaCl only and with a mixture of NaCl and charged nanoparticles. These systems are studied using two levels of description, all-atom explicit water molecular dynamics (MD) simulations and coarse-grained implicit solvent MD simulations. The charge density and electric potential profiles and current-voltage relationship predicted by the implicit solvent simulations with ϵ = 11.3 show good agreement with the predictions from the explicit water simulations. Under nonequilibrium conditions, the predictions of the implicit solvent simulations with a dielectric constant closer to the one of bulk water are significantly different from the predictions obtained with the explicit water model. These findings are closely aligned with experimental data on the dielectric constant of water when confined to nanometric spaces, which suggests that ϵ decreases significantly compared to its value in the bulk. Moreover, the largest electric current rectification is observed in systems containing nanoparticles when ϵ = 78.8. Using enhanced sampling, we have shown that this larger rectification arises from the presence of a significantly deeper minimum in the free energy of the system with a larger ϵ, and when a negative voltage bias is applied. Since implicit solvent models and mean-field continuum theories are often used to design Janus membranes based on bipolar nanopores, this work highlights the importance of properly accounting for the effects of confinement on the dielectric constant of the electrolyte solvent. The results presented here indicate that the dielectric constant in implicit solvent simulations may be used as an adjustable parameter to approximately account for the effects of nanometric confinement on aqueous electrolyte solvents.

Research on Leakage Current Waveform Spectrum Characteristics of Artificial Pollution Composite Insulator

In order to know about the change features of leakage current during the pollution flashover process of composite insulators, the study of the pollution flashover test on composite insulator under the pollutional condition is presented in the artificial fog cabinet. The characteristics of leakage current waveforms in time-domain and frequency-domain are measured and analyzed during the test. The analysis results show that there is a strong correlation among the fundamental harmonic, the third harmonic and fifth harmonic. The characteristics of leakage current spectrum are represented by the maximum value of leakage current (Im), total harmonic distortion (THD), and phase difference of fundamental leakage current (θ). During a near-flash event, the leakage current exhibits high amplitude, low harmonic content, and small phase difference between the fundamental leakage current and voltage. The research findings provide a basis for establishing a pollution flash warning system based on leakage current characteristic quantities.

A Novel High-Impedance Fault Detection Technique in Smart Active Distribution Systems

Identification of high impedance fault (HIF) is important in smart active distribution systems (SADSs). The existing protection methods fail to detect HIF, as HIFs have peculiar fault current characteristics. However, if HIFs are left undetected, they result in severe fire hazards and arcing. The paper proposes a novel fault detection indicator that utilizes the differential energy associated with the positive sequence current components during faults. IEEE-13 bus and IEEE-34 bus system is used for simulation in Real Time Digital Simulator (RTDS). The results show that proposed technique accurately identify HIFs and perfectly discriminates the transients due to HIFs, non-linear loads and voltage and reactive power compensation devices. Furthermore, it differentiates HIFs from other switching transients like capacitor or load switching events. Other factors, like transformer inrush currents, effect of noise and sampling rate are also considered to ensure the accuracy and reliability of the proposed method. Moreover, the practical feasibility of the proposed method is also experimentally validated.

Numerical Study on Fault Current Characteristics of Self-Shielded HTS DC Cables Made of REBCO Tapes in Parallel With Stainless Steel Tapes

Numerical Study on Fault Current Characteristics of Self-Shielded HTS DC Cables Made of REBCO Tapes in Parallel With Stainless Steel Tapes

Fault Current Characteristics of Self-Shielding HTS DC Cable Made of REBCO Tapes

Fault Current Characteristics of Self-Shielding HTS DC Cable Made of REBCO Tapes

Performance assessment of Si based dual metal double gate vertical TFET biosensor

This piece of work highlights the application of dual-metal double-gate VTFET as label free biosensor having enhanced switching ratio, current driving capability and sub-threshold swing and consequently high sensitivity. The use of dual-material namely tunneling gate and auxiliary gate in this device leads to high switching ratio (ION/IOFF) and low sub-threshold swing (SS). In order to observe outcome of this suggested biosensor, various biomolecules dielectric constant have been considered and examined with respect to electric field, energy band diagram, drain current characteristics and sub-threshold potential profile. Neutral biomolecules with a higher dielectric constant exhibits greater drain current sensitivity against biomolecules having lower dielectric constant. Here effect of cavity interface charge on the sensitivity performance of the proposed biosensor device is also verified. This fabrication feasible homo vertical TFET based biosensor gives best sensitivity performance for K = 12, both for the current (5.44 × 105) and transconductance (3.14 × 105) with the minimal sub-threshold swing of 9.9 mV/decade. Silvaco, a commercially accessible TCAD tool is used to investigate the proposed structure.

Current Distribution and Critical Current Characteristics of a Novel HTS Cable Woven by Transpositional REBCO Tapes

Current Distribution and Critical Current Characteristics of a Novel HTS Cable Woven by Transpositional REBCO Tapes

청소년 도박 실태 및 치료방법 고찰

Adolescence is a period with important developmental changes and growth. Due to neurobiological vulnerability and impulsivity related to ongoing brain development, adolescents exhibit a high rate of risky behaviors such as gambling. In addition, adolescent gambling has recently emerged as a serious social problem because easily accessible channels through online have increased. Adolescent gambling can cause a number of serious problems, including school adjustment problems, financial problems, interpersonal problems, delinquent behaviors, and coexistence of mental illnesses such as substance addiction and depression. Thus, an in-depth understanding of adolescent gambling is required. This study aims to systematically review current status, characteristics, risk factors, treatment, and prevention of adolescent gambling. Future directions for adolescent gambling research are also suggested.